Ask stories

What are your predictions for this coming year?

With the explosion of AI tools in our workflows this year, I stopped using Stack Overflow and copilot.

Previously, SO was an unavoidable step of my programming effort for navigating or learning new frameworks, for exploring solutions, for debugging strange cases.... But now , it has been a long while since I visited the site.

Are you still using SO, reading, searching, contributing?

It's the time of the year again, so I'd be interested hear what new (and old) ideas have come up. Previously asked on:

2024 → https://news.ycombinator.com/item?id=42373343

2023 → https://news.ycombinator.com/item?id=38467691

2022 → https://news.ycombinator.com/item?id=34190421

2021 → https://news.ycombinator.com/item?id=29667095

2020 → https://news.ycombinator.com/item?id=24947167

2019 → https://news.ycombinator.com/item?id=20899863

2018 → https://news.ycombinator.com/item?id=17790306

2017 → https://news.ycombinator.com/item?id=15148804

Let's assume you're writing Go, Python, or any other language in which `import` is a reserved keyword. Let's assume also that you're writing a new package, whose purpose is to "import" data.

What do you name this package?

Our team went through this exercise semi-recently, and we're curious about how everyone else would think about it. Here's a (non-exhaustive) list of options we considered: imports, ingest, dataimport, ímport, impørt.

- HN errored on all authenticated requests with 502 Bad Gateway. It did still respond to a limited amount of unauthenticated requests with presumably cached pages, which did not get updated. The last post on /newest claimed "0 minutes ago", but was actually much older (1:32:57 PM GMT) and not the newest post.

- This status page actually identified the outage: https://hackernews.onlineornot.com/ - Pages by Hund and Statuspal did not show the outage.

- The last post before the outage was https://news.ycombinator.com/item?id=46301823 (1:39:59 PM GMT). The last comment was https://news.ycombinator.com/item?id=46301848 (1:41:54 PM GMT).

- There was an average of ~4 seconds per comment just prior to the outage. Based on this, HN likely went down at 1:41:58 PM GMT.

What are you working on? Any new ideas that you're thinking about?

This happened to me, and it's about to happen again soon.

Someone has submitted a 4k-line PR to one of my projects.

The person is a long-time user and is very enthusiastic about the app. They wanted a feature they've been asking about for half a year.

Not sure what to do now. I really want to help my user, but I don't like this code in my codebase.

This morning, I received another message from another user who is about to submit one more feature.

Is there any polite way to prevent that?

When working on my projects and talking to investors, I often hear: “Just post it on Hacker News or Reddit and show that people love it.”

What I find strange is that Hacker News feels oddly opaque. I’ve never met anyone who can clearly explain how it works in practice. Not just the rules, but the dynamics: what’s repeatable, what’s luck, and what actually matters.

By using the Kevin Bacon-number idea: I can usually get within three degrees of separation of well-known technologists like Linus Torvalds, but I can’t seem to get within three steps of someone who confidently understands how HN works.

So I’m asking sincerely: Does anyone here feel they understand Hacker News? If so, what are the real levers, and what do people consistently misunderstand?

PS: This question comes from a mix of genuine curiosity and personal frustration. I’m honestly trying to understand how HN works in practice.

Working on automating small business finance (bookkeeping, reconciliation, basic reporting).

One thing I keep noticing: compared to programming, accounting often looks like the more automatable problem:

It’s rule-based Double entry, charts of accounts, tax rules, materiality thresholds. For most day-to-day transactions you’re not inventing new logic, you’re applying existing rules.

It’s verifiable The books either balance or they don’t. Ledgers either reconcile or they don’t. There’s almost always a “ground truth” to compare against (bank feeds, statements, prior periods).

It’s boring and repetitive Same vendors, same categories, same patterns every month. Humans hate this work. Software loves it.

With accounting, at least at the small-business level, most of the work feels like:

normalize data from banks / cards / invoices

apply deterministic or configurable rules

surface exceptions for human review

run consistency checks and reports

The truly hard parts (tax strategy, edge cases, messy history, talking to authorities) are a smaller fraction of the total hours but require humans. The grind is in the repetitive, rule-based stuff.

When Excel formulas get large, I often lose track of what’s actually happening.

I’m wondering whether representing formulas structurally (instead of plain text) could make them easier to read and modify, but I’m not sure if this really helps in practice.

How do you usually handle large formulas?

I see this as becoming part of "The Borg", I doubt I'd be down with it. But I want to know how other people feel. The idea is open to interpretation - my view is its basically augmenting your cognition with AGI-cloud, so rather than going through a device, it can "live next to your thoughts", and you can access it at will.

I’m releasing *Framework Shells* (`fws`): a standalone Python package for orchestrating long-running background processes (“shells”) with *PTY*, *pipes*, and *dtach* backends.

This is meant for environments where you don’t want to stand up a full supervisor stack (or don’t have one): quick multi-service prototypes, dev environments, constrained userlands, etc.

### What it does

* Spawn/manage shells with:

  * **PTY**: interactive terminal sessions (resize, input, stream)
  * **Pipes**: stdin/stdout/stderr streams (good for daemons/LSPs)
  * **dtach**: persistent sessions you can attach/detach to (survives manager restarts)

### CLI quickstart

```bash # list shells fws list

# run a one-off shell (no spec) fws run --backend pty --label demo -- bash -l -i

# apply a YAML shellspec (recommended) fws up shells.yaml

# terminate shells fws down

# attach to a dtach-backed shell fws attach <shell_id>

# show managed shells + procfs descendants fws tree --depth 4 ```

### Shellspec example

```yaml version: "1" shells: worker: backend: proc cwd: ${ctx:PROJECT_ROOT} subgroups: ["worker", "project:${ctx:APP_ID}"] command: ["python", "-m", "your_module.worker", "--port", "${free_port}"] ```

### Isolation + security model (simple by default)

* `FRAMEWORK_SHELLS_SECRET` derives the `runtime_id` (namespace) and API tokens. * If the secret is set, mutating API endpoints require:

  * `Authorization: Bearer <token>` (or `X-Framework-Key`).

Hard limit: if two runtimes share the same OS user/UID, the OS may still allow signaling each other’s processes. The guarantee is: no cross-count/adopt/control *through the library’s control plane*.

### Real-world usage

I use this as the substrate of a full dev environment where “apps are shells” (terminals, IDE + LSP, agent/MCP, aria2 RPC, file explorer, llama.cpp runner, etc.). Repo:

```text https://github.com/mrsurge/termux-extensions-2 ```

### Feedback I want

* Does the secret/fingerprint/runtime isolation contract feel right? * Any obvious foot-guns in the default API/CLI? * Expectations vs systemd/supervisord/tmux/dtach: where would you use this?

github.com/mrsurge/framework-shells

pip install "framework-shells @ git+https://github.com/mrsurge/framework-shells@main"

```bash fws --help ```

Hi HN — I’ve wanted to start a personal blog for a few years, but I keep hesitating.

I write a lot privately (notes, mini-essays, thinking-through problems). Paul Graham’s idea that essays are a way to learn really resonates with me. But I rarely publish anything beyond occasional LinkedIn posts.

My blockers:

•“Nobody needs this” / “It’s not original”

•“AI can explain most topics better than I can”

•A bit of fear: shipping something that feels naive or low-signal

At the same time, I read a lot of personal blogs + LinkedIn and I do get real value from them — mostly from perspective, lived experience, and clear thinking, not novelty.

For those of you who blog (or used to):

•What made it worth it for you?

•What kinds of posts actually worked (for learning, career, network, opportunities)?

•Any practical format that lowers the bar (length, cadence, themes)?

•If you were starting today, what would you do differently?

I’m not trying to build a media business — more like building a “public notebook” that compounds over years.

On teams I’ve worked with, we often run into systems where nobody really knows why certain configs, services, or architectural choices exist. Docs are outdated, Slack history is messy, and the people who made the decision are often gone. When something breaks, we end up rediscovering the same context over and over. Is this just inevitable on long-lived systems, or do experienced teams have a better way of preserving this kind of context?

I feel like reading HN sometimes there is the assumption that everyone who is a programmer by default works on web stuff (front end/back end).

I'm curious to hear about what other jobs/domains exist outside of this and how it is working on non-web stuff.

Here's a video from 2004 https://www.youtube.com/watch?v=Y1J9kfDCAmU

It's his 100th birthday today.

I’ve been working on a small language learning app as a solo developer.

I intentionally avoided gamification, streaks, subscriptions, and engagement tricks. The goal was calm learning — fewer distractions, more focus.

I’m starting to wonder if this approach is fundamentally at odds with today’s market.

For those who’ve built or used learning tools: – Does “calm” resonate, or is it too niche? – What trade-offs have you seen when avoiding gamification?

Not here to promote — genuinely looking for perspective.

I'm wondering if anyone is actually using LLMs to process documents reliably in production. One hallucination could lead to a host of issues. For example, if someone is using LLMs to process documents and enter data into an ERP, if even one number is off it could cause accounting issues, inventory issues etc. Human in the loop doesn't help because the human would just have to read the document themselves to ensure accuracy, defeating the point of the automation.

I've been on a business trip this week, and sitting on the plane, I was randomly browsing NYT and read this article which really REALLY pissed me off: https://www.nytimes.com/2025/12/14/us/fire-department-software-private-equity.html?unlocked_article_code=1.8k8.yzeR.NwSK3PTQeXQj&smid=nytcore-android-share

TLDR: Private equity is buying up all these software vendors, and preying upon vulnerable fire departments; one rural department with a total budget of $130k/yr saw their software costs go up 3x in one year (from $4k/yr to $12k/yr).

I want to do something. I have not worked in the emergency services domain before, so I know that I am naive. I do have experience with oncall and mission-critical software maintenance and highly available/durable services, but when I say mission critical I mean millions-of-dollars at risk, not human lives.

I want to solicit HN for very early directional advice, of any and all kinds.

- Are there some existing open source projects or foundations with a mission like this, to serve and protect critical services like emergency response?

- Is it feasible to build incrementally, i.e. ship small components of incremental value, and would fire departments be open to trying an open source option?

- Are there things like certifications or regulatory hurdles, that might be expensive to get?

- Does anyone randomly happen to have experience in this industry, and would be willing to write up their perspective?

My early initial thesis is something like this: I personally cannot stomach the idea of simply passively "letting" private equity invade this aspect of society, to hold emergency services departments and by extension taxpayers hostage. They are essentially extorting and exploiting society's inelastic demand for emergency fucking services. So I don't care about making profit, I only care about actually solving the needs of the emergency departments and of protecting human life (knowing that I am naive still, I definitely do not want to overpromise and put lives at risk). But my personal feelings aside, I do think there is a useful insight here: if useful software can be made reliably and cheaply, by engineers motivated to help their communities instead of profit (or just to poke private equity in the eye), then ultimately private equity cannot compete against an adversary that doesn't care about profit -- we actually CAN WIN, because eventually they will give up and exit these industries if they see that there is no profit to squeeze.

I am looking for like-minded builders. I seriously think the software foundation could simply be a vehicle for early-retirement rich FIREd ex-techies, to add some new purpose in their lives, by using their skills to solve a targeted and well-scoped set of problems.

"Some men aren't looking for anything logical, like money. They can't be bought, bullied, reasoned, or negotiated with. Some men just want to watch the world [NOT] burn [because the fire departments should have cheap reliable emergency services software]." -- Alfred Pennyworth, The Dark Knight

"Beware the fury of a patient man." -- John Dryden

I am a patient man, with a newly gained cold fury. I am willing to write code. Or organize a software foundation. Or be an investor/funder for someone else to write the software. Or whatever form of help I can give.

Appreciate any and all help or feedback (positive or negative)!

I read recently a post here in HN about this topic but I can't find it anymore so I'm writing here my thoughts.

Recently, I started a hobby project in Rust that collects some news from several websites and creates me a weekly digest.

Since I'm making it for fun I started developing a scraper.

However, one simpler option was to use the websites' RSS feed. So, I looked for them as well but few websites have them.

Now, with the advent of Agentic AI they seem to be an old fashioned way that is needed anymore.

What do you think?

I’ve been working in analytics and advanced analytics for about 6 years. I started in a large consultancy and later went solo, so I’ve seen both enterprise and smaller product teams up close.

Something keeps bothering me. In most projects, analytics feels like infrastructure that no one is genuinely excited about. People rarely want to invest in it when building a product. It’s treated as something you should have, not something you want to have.

Teams are “happy” to pay for software development, advertising, copywriting, design. Those are seen as directly useful. Analytics (GA4, event tracking, or even more structured setups like CDPs) is often perceived as background noise, necessary to keep the engine running, but not something that meaningfully moves the product forward day to day.

In practice, many teams end up using only a handful of metrics to make decisions, even when a complex analytics stack exists underneath. The rest is there “just in case.”

I’m curious whether others see the same pattern. Is analytics undervalued because its ROI is indirect and delayed? Or is most analytics work simply over-engineered for the actual decisions teams make? At what point does analytics shift from “necessary plumbing” to a real competitive advantage?

Would love to hear perspectives from founders, engineers, and product folks who’ve built and scaled things.

We're a very small startup with a web-based application written in React. Every non-engineer in the company spends a lot of time making screens in Lovable and thinks we can and should just "take that" and drop it on the site. We fight back, but even when we just use it as a design inspiration we're left with terrible UX, vastly different pages and a genuinely bad product that's just good enough not to be seen as a problem by the rest of the team. Help me make the case that we need a product designer, graphic designer, and to use these tools for what they're worth.

Don't worry - self-hosted runners are fine.

I'm an indie developer who has built several free-to-use tool applications that I plan to monetize through advertising once they gain enough users. My dilemma is whether to open source these products now, or wait until they're more established.

Is there any specific program / college / etc outside of tech that you would want to study if you could?

I struggle to find the right way to provide feedback on pull requests (PRs) that mostly consist of AI generated code. Co-workers submitting them have learned to disclose this -- I found it frustrating when they didn't -- and now say they have reviewed and iterated on it. But often the result is still what I would describe as "a big contribution off the mark", meaning a lot of code that just follows the wrong approach.

Usually, when someone does a lot of work, which we used to be able to measure in lines of code, it would seem unfair to criticize them afterwards. A good development process with ticket discussions would ensure that someone doesn't do a lot of work before there is agreement on the general approach. But now, with AI, this script no longer works, partially because it's "too easy" to do it before even deciding this.

So I'm asking myself and now HN: is it OK to point out when an entire PR as such is garbage and should simply be discarded? How can I tell how much "brain juice" a co-worker has spent on it and how attached they might be to it by now if I don't even know whether they even know the code they submitted or not?

I have to admit that I hate reviewing huge PRs and the problem with AI generated code is that often it would have been much better to find and use an existing open-source library to get the task done rather than (re-)generate a lot of code for it. But how will I know this until I've actually taken the time to review and understand the big, new proposed contributions? And even if I now do spend the time to actually understand the code and implied approach, how will I know which part of it reflects their genuine opinion and intellect (which I'd be hesitant to criticize) and what is AI-fluff I can rip apart without stepping on their toes? If the answer is "let's have a meeting", then I'd say the process has failed.

Not sure there is a right answer here, but I would love to hear people's take on this.

This is something I’ve noticed about myself and I’m curious about the underlying mechanism.

Whenever I receive a letter or email that looks official — from a bank, government office, school, etc. — I feel a spike of anxiety almost immediately. What’s strange is that this happens before I even know what the message actually says.

In most cases, it turns out to be routine or harmless. Still, the anxious reaction comes first and sometimes lingers until I fully understand the content.

I’m not looking for personal advice, but I’m curious whether this response is tied to how humans process authority, uncertainty, or perceived consequences. Is there any psychological or cognitive explanation for why the anticipation alone triggers stress, even when experience says it’s usually nothing serious?

If you have a iPhone which supports IOS 26.X but is on IOS 18 they aren’t showing the latest security update for 18. On my iPhone 13 it only showed the 26.2 update. To get it to offer the 18.7.3 update switch your update settings to “IOS 18 Developer Beta”.

I personally like to stay one major version behind these days as Apples software quality has gone a bit downhill. It’s a really bad look trying to force people into a major version upgrade when a patch release is available. Not sure what drove the decision to not show both options like they used to.

Figured I would let the community know how to get the patch version instead.

I've been working on a personal project recently, rewriting an old jQuery + Django project into SvelteKit. The main work is translating the UI templates into idiomatic SvelteKit while maintaining the original styling. This includes things like using semantic HTML instead of div-spamming, not wrapping divs in divs in divs, and replacing bootstrap with minimal tailwind. It also includes some logic refactors, to maintain the original functionality but rewritten to avoid years of code debt. Things like replacing templates using boolean flags for multiple views with composable Svelte components.

I've had a fairly steady process for doing this: look at each route defined in Django, build out my `+page.server.ts`, and then split each major section of the page into a Svelte component with a matching Storybook story. It takes a lot of time to do this, since I have to ensure I'm not just copying the template but rather recreating it in a more idiomatic style.

This kind of work seems like a great use case for AI assisted programming, but I've failed to use it effectively. At most, I can only get Claude Code to recreate some slightly less spaghetti code in Svelte. Simple prompting just isn't able to get AI's code quality within 90% of what I'd write by hand. Ideally, AI could get it's code to something I could review manually in 15-20 minutes, which would massively speed up the time spent on this project (right now it takes me 1-2 hours to properly translate a route).

Do you guys have tips or suggestions on how to improve my efficiency and code quality with AI?